Adaptive Lag Synchronization of Memristive Neural Networks With Mixed Delays | Zendy

Chuan Chen | Zendy; Lixiang Li | Zendy; Haipeng Peng | Zendy; Yixian Yang | Zendy

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Adaptive Lag Synchronization of Memristive Neural Networks With Mixed Delays

Author(s) -

Chuan Chen,

Lixiang Li,

Haipeng Peng,

Yixian Yang

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2858246

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This paper investigates the lag synchronization of memristive neural networks (MNNs) with mixed delays via adaptive control. Based on the switching jump properties of memristors and the assumption that the activation functions are bounded, three lemmas are derived first to deal with the theoretical analysis difficulties caused by the existences of time delays and time lag. By designing a series of suitable adaptive controllers, we prove that the considered MNNs can achieve asymptotic lag synchronization, exponential lag synchronization, and finite-time lag synchronization, respectively. Adaptive control can avoid the large control gains very well, and adaptive control can be used even when the system parameters are unknown. Moreover, extra calculations are not required to determine the appropriate control gains. Numerical simulations are presented to verify the effectiveness of the obtained theoretical results.

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